A New Algorithm for Hand Gesture Recognition in Color Videos for Operating System Commands

Maziyar Grami
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Abstract

In recent years, human-computer interaction and machine vision have become two of the favorite research areas in computer science. This paper is research on hand motion and hand gesture recognition using image processing techniques to control some system commands. Different hand motion and gesture recognition methods have been considered by researchers for use in computer systems, video game consoles, and mobile devices. In such cases, hand motion or hand gesture type is detected by tracking the hands' image or by matching the image with gestures storing in the database, after the first position of the hand is identified. In this paper, we provide an efficient way for recognizing and tracking the sequences of image frames. The main objective of this paper is to provide an efficient method for hand recognition in crowded environments, without any restrictions. The frames can be received from a video file. In the first frame, the location of the hand is recognized using color analysis, then it would be compared to the next frames. Detected movements are applied for controlling commands in an operating system. So far, an effective way for this kind of problem has not been suggested. In this study, we have tried to propose an efficient algorithm that is less dependent on background and lighting conditions. We tested the proposed method on several captured videos using the Image Processing Toolbox of MATLAB. These videos are captured in very crowded environments. The presented results showed that in different lighting conditions and various noises, the proposed method works almost without mistakes.
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基于操作系统命令的彩色视频手势识别新算法
近年来,人机交互和机器视觉已成为计算机科学中两个热门的研究领域。本文研究了用图像处理技术来控制系统指令的手部运动和手势识别。研究人员已经考虑了不同的手部运动和手势识别方法,用于计算机系统、视频游戏机和移动设备。在这种情况下,在识别手的第一个位置后,通过跟踪手的图像或将图像与存储在数据库中的手势进行匹配来检测手的运动或手势类型。在本文中,我们提供了一种有效的方法来识别和跟踪图像帧序列。本文的主要目的是提供一种在拥挤环境中不受任何限制的有效的手部识别方法。帧可以从视频文件中接收。在第一帧中,使用颜色分析识别手的位置,然后将其与下一帧进行比较。检测到的移动应用于操作系统中的控制命令。到目前为止,还没有提出解决这类问题的有效方法。在本研究中,我们试图提出一种对背景和光照条件依赖性较小的高效算法。我们使用MATLAB的图像处理工具箱对几个捕获的视频进行了测试。这些视频是在非常拥挤的环境中拍摄的。实验结果表明,在不同的光照条件和不同的噪声条件下,该方法几乎没有误差。
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